Statistical Methods for Neural Mechanisms Mediating Cognitive System in Mental Health Research

心理健康研究中调节认知系统的神经机制的统计方法

• 批准号: 9278065
• 负责人: SEONJOO LEE
• 金额: $ 13.14万
• 依托单位: NEW YORK STATE PSYCHIATRIC INSTITUTE DBA RESEARCH FOUNDATION FOR MENTAL HYGIENE, INC
• 依托单位国家: 美国
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-09-30 至 2019-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9278065
• 关键词: Adult; Affect; Age; Age-associated memory impairment; Aging; Alzheimer' s Disease; Applications Grants; Award; Biological Neural Networks; Biometry; Brain; Brain imaging; Cognition; Cognition Disorders; Cognitive; Cognitive aging; Data; Data Set; Data Sources; Development; Early Diagnosis; Elderly; Episodic memory; Functional Magnetic Resonance Imaging; Goals; Heterogeneity; Image; Impaired cognition; Liquid substance; Machine Learning; Magnetic Resonance Imaging; Measurement; Measures; Mediating; Mediation; Mediator of activation protein; Mental Health; Mental disorders; Mentors; Methods; Modality; Modeling; Multicenter Studies; Nerve Degeneration; Neurosciences; Pathology; Pattern; Performance; Psychiatry; Psychopathology; Research; Role; Speed; Statistical Data Interpretation; Statistical Methods; Structure; System; Techniques; Testing; Training; age effect; age related; analytical tool; brain volume; career; cerebral atrophy; cognitive ability; cognitive change; cognitive system; cognitive task; cognitive testing; imaging study; method development; mild cognitive impairment; multimodality; neuroimaging; neuromechanism; normal aging; novel; pathological aging; public health relevance; relating to nervous system; research and development; tool

 DESCRIPTION (provided by applicant): Psychiatric disorders, as well as normal aging, are often associated with a wide range of cognitive changes. Recent developments in neuroscience, particularly multimodal neuroimaging techniques, can provide better understanding of neural mechanisms that underlie these changes. Mediation analysis is a popularly used statistical method to investigate neural mechanisms. However, existing statistical methods were not designed to accommodate such large-scale, multi-dimensional, and complicated data in mediation analysis. The overarching aim of my K01 Mentored Research Development Award is to acquire training that will allow me to pursue a line of mental health research related to cognition and to develop novel statistical methods to support the emerging research in cognitive neuroimaging and mental health. I propose to receive training in: 1) cognition and its relationship with aging and psychopathology; 2) neural basis in cognition and multimodal neuroimaging; 3) functional mediation and selective mediation analysis. This will provide me with the tools to conduct research that will fill significant gaps in the statistical analyses on cognitive neuroimaging, particularly focusing on aging and neurodegeneration-associated cognitive decline: First, I propose to review and develop analytic tools to examine how aging and psychopathology affect cognitive system constructs. Understanding the patterns of age-related differences in each of these cognitive constructs and the possible heterogeneity related to the psychopathology is of great importance. I will test nonlinearity and heterogeneity in the latent cognitive constructs using two independent large data. Second, I will develop and examine activation networks (reference ability neural networks (RANNs)) associated with each of the cognitive constructs. Although it is critical to understand underlying neural networks of cognition, there are many unsolved problems in investigating the presence or structure of RANNs. I will develop a method to derive underlying networks, find RANNs taking into account possible spatial overlap among RANNs, and investigate the relationship between RANNs expression and performance on the concomitant cognitive constructs. Third, I will develop selective mediation analyses to examine the relationship between imaged neural substrates of aging and psychiatric disorder, such as regional volume loss, and cognitive decline and test if the different imaged brain modalities selectively mediate cognitive aging by influencing the expression of cognitive ability constructs. In totality, this training and research will inform hypotheses for an R01 grant application to be submitted in Year 4 of the award period. While to date I have exemplified a productive research career in biostatistics and psychiatry, I need substantially more training for successful completion of the research proposed in this application and to make a lasting contribution to the field of mental health.

 描述（由适用提供）：精神疾病以及正常衰老通常与广泛的认知变化有关。神经科学的最新发展，尤其是多模式神经影像学技术，可以更好地了解这些变化的神经元机制。调解分析是一种流行的使用统计方法，用于研究神经元机制。但是，现有的统计方法并非旨在适应调解分析中的大规模，多维和复杂数据。我的K01指导研究发展奖的总体目的是获得培训，这将使我能够追求与认知有关的心理健康研究，并开发新颖的统计方法，以支持认知神经影像学和心理健康方面的新兴研究。我建议接受：1）认知及其与衰老和心理病理学的关系； 2）认知和多模式神经影像学的神经元基础； 3）功能中介和选择性调解分析。这将为我提供进行研究的工具，这些工具将填补有关认知神经影像学的统计分析的巨大空白，尤其是专注于衰老和与神经变性相关的认知下降：首先，我提出了审查和开发分析工具以检查衰老和精神病理学如何影响认知系统结构的分析工具。了解这些认知构建中的每一个中与年龄相关的差异的模式以及与心理病理学相关的可能异质性非常重要。我将使用两个独立的大数据测试潜在认知构建体中的非线性和异质性。其次，我将开发并检查与每个认知构建体相关的激活网络（参考能力神经网络（RANN））。尽管了解基本的认知神经网络至关重要，但是在研究兰斯的存在或结构时仍存在许多未解决的问题。我将开发一种方法来得出潜在的网络，发现Ranns考虑RANN之间可能的空间重叠，并研究RANNS表达与伴随认知构建体的性能之间的关系。第三，我将开发选择性的调解分析，以检查成像的衰老和精神疾病的神经底物之间的关系，例如区域体积损失，认知能力下降，并测试是否通过影响认知能力构建体的表达选择了不同成像的脑形态。总体而言，这项培训和研究将为假设提供有关R01赠款申请的假设，将在奖励期的第4年提交。迄今为止，我已经体现了生物统计学和精神病学领域的一项富有成效的研究职业，但我需要更多的培训才能成功完成本应用程序中提出的研究，并对心理健康领域做出持久的贡献。